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"
+ ],
+ "text/plain": [
+ " Date Open High Low Close Adj Close \\\n",
+ "ticker \n",
+ "A 2000-01-03 56.330471 56.464592 48.193848 51.502148 43.463024 \n",
+ "A 2000-01-04 48.730328 49.266811 46.316166 47.567955 40.142933 \n",
+ "A 2000-01-05 47.389126 47.567955 43.141991 44.617310 37.652870 \n",
+ "A 2000-01-06 44.080830 44.349072 41.577251 42.918453 36.219185 \n",
+ "A 2000-01-07 42.247852 47.165592 42.203148 46.494991 39.237453 \n",
+ "\n",
+ " Volume sector subsector year \n",
+ "ticker \n",
+ "A 4674353 Health Care Life Sciences Tools & Services 2000 \n",
+ "A 4765083 Health Care Life Sciences Tools & Services 2000 \n",
+ "A 5758642 Health Care Life Sciences Tools & Services 2000 \n",
+ "A 2534434 Health Care Life Sciences Tools & Services 2000 \n",
+ "A 2819626 Health Care Life Sciences Tools & Services 2000 "
+ ]
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
- "import os\n",
"from glob import glob\n",
"\n",
"# Write your code below.\n",
- "\n"
+ "\n",
+ "# Step 1: Load all parquet files into a single DataFrame\n",
+ "parquet_files = glob(os.path.join(price_data_dir, \"**\", \"*.parquet\"), recursive=True)\n",
+ "parquet_files = [f for f in parquet_files if os.path.isfile(f)]\n",
+ "\n",
+ "# Load data without transformations, just to verify structure\n",
+ "df = dd.read_parquet(parquet_files, engine=\"pyarrow\")\n",
+ "\n",
+ "# Step 2: Verify loaded columns and initial rows\n",
+ "print(\"Loaded columns:\", df.columns)\n",
+ "df.head()"
]
},
{
@@ -88,11 +293,224188 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": null,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Close_lag'] = df.groupby(\"ticker\")['Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:14: UserWarning: `meta` is not specified, inferred from partial data. Please provide `meta` if the result is unexpected.\n",
+ " Before: .shift(1)\n",
+ " After: .shift(1, meta={'x': 'f8', 'y': 'f8'}) for dataframe result\n",
+ " or: .shift(1, meta=('x', 'f8')) for series result\n",
+ " df['Adj_Close_lag'] = df.groupby(\"ticker\")['Adj Close'].shift(1)\n",
+ "/tmp/ipykernel_56322/421061092.py:13: UserWarning: `meta` is not specified, inferred from partial data. Please pr